Evaluation of decay photocurrent measurements in dye‐sensitized solar cells: Application to laser beam‐induced current technique

The use of the laser beam‐induced current (LBIC) technique in photovoltaic devices is widespread, but its use in photoelectrochemical cells, such as dye‐sensitized solar cells (DSSCs), is limited due to the configuration of these devices. The main reason is the very slow response time of DSSCs in the decay process, and therefore LBIC scans take too long to perform. We have designed a procedure published in the literature to correct the photocurrent values obtained by the LBIC technique, based on an algorithm that uses a decreasing mono‐exponential model. This work presents a study of the decay measurements in DSSCs using several functions, in order to improve the algorithm designed. It concludes that functions such as a decreasing bi‐exponential or Becquerel function generate better fits to experimental data. Copyright © 2010 John Wiley & Sons, Ltd.     

Determination of supercapacitor parameters based on fractional differential equations

In this paper, we estimate the parameter values of a fractional-order model of supercapacitors involving fractional derivatives of Liouville-Caputo, Caputo-Fabrizio, and Atangana-Baleanu and fractional conformable derivative in the Liouville-Caputo sense. We present the exact solution of the considered model using the properties of the Laplace transform operator together with the convolution theorem. They developed numerical simulations using each one of the fractional derivatives; the results were compared graphically with experimental data obtained from different supercapacitors using standard laboratory equipment. The nonlocal parameters involved in the equivalent electrical circuit for the supercapacitor model are recalculated for each fractional derivative using a particle swarm optimization algorithm for generating optimal solutions.     

Complete convergence of stochastic approximation algorithm in ℝd under random noises

In this article, we study a stochastic approximation algorithm that approximates the exact root θ of a function M defined in ?^d into ?^d. The function M cannot be known exactly, but only noisy measurements are available at each point x_n with the error ξ_n. The sequence of noise (_ξn)n is random; we treat both cases where it is independent and dependent and we establish the complete convergence of the approximated sequence of θ.     

Controller design for distributed parameter systems with time delays in the boundary feedbacks via the backstepping method

For a distributed parameter system with an input delay in the boundary, a feedback control law is presented by means of the backstepping method. The square integrability of input signal is verified based on the target system. Then, the boundedness and invertibility of the corresponding backstepping transformation are proved under the regularity of system and the admissibility of feedback operator. Thus, the resulting closed-loop system is shown to be exponentially stable. Finally, as an application, a numerical simulation of a one-dimensional Schrödinger equation with a delay input is carried out, and the simulation results demonstrate the effectiveness of the suggested control law.     

AlGaN/GaN HEMT结构热时间常数谱提取方法的研究

利用电学法对AlGaN/GaN 高电子迁移率晶体管(HEMTs)有源区瞬态温升进行测量.利用非参数拟合算法—局部加权回归散点平滑法(LOWESS)对原始测量数据进行平滑去噪处理,进而得到热时间常数谱,分析AlGaN/GaN HEMTs热传导路径物理结构。与传统平滑去噪方法—多阶指数拟合相比,通过LOWESS算法得到的热时间常数谱更丰富,得到RC网络更多,进而热传导路径结构分析更精细。结果表明,LOWESS非参数拟合算法能够更好的去除测量数据噪声,保留原始离散数据细微的变化趋势。通过该方法所提取的热时间常数谱能描述AlGaN/GaN HEMTs有源区温度细微变化,帮助研究人员精确分析热传导路径层次构成。     

Cumulative Sum Control Charts for Monitoring Weibull‐distributed Time Between Events

The Weibull distribution can be used to effectively model many different failure mechanisms due to its inherent flexibility through the appropriate selection of a shape and a scale parameter. In this paper, we evaluate and compare the performance of three cumulative sum (CUSUM) control charts to monitor Weibull‐distributed time‐between‐event observations. The first two methods are the Weibull CUSUM chart and the exponential CUSUM (ECUSUM) chart. The latter is considered in literature to be robust to the assumption of the exponential distribution when observations have a Weibull distribution. For the third CUSUM chart included in this study, an adjustment in the design of the ECUSUM chart is used to account for the true underlying time‐between‐event distribution. This adjustment allows for the adjusted ECUSUM chart to be directly comparable to the Weibull CUSUM chart. By comparing the zero‐state average run length and average time to signal performance of the three charts, the ECUSUM chart is shown to be much less robust to departures from the exponential distribution than was previously claimed in the literature. We demonstrate the advantages of using one of the other two charts, which show surprisingly similar performance. Copyright © 2014 John Wiley & Sons, Ltd.     

基于无噪后验错误矢量信号能量的变正则因子仿射投影算法

变正则因子技术是提高仿射投影自适应算法性能的重要方法之一.由于环境噪声的影响,现有的变正则因子自适应算法收敛速度较慢且稳态误差较大,各种测量、评估误差的存在进一步恶化了算法性能.为提高自适应算法的跟踪性能,本文在分析无噪先验错误矢量、无噪后验错误矢量和额外均方错误间关系的基础上,提出通过最小化无噪后验错误矢量信号能量来推导自适应变正则因子表达式的方法.在实践应用中,该方法利用了测量噪声的统计方差特性,并提出一种更加光滑且更加容易控制的指数缩放因子评估方法.系统辨识的仿真结果表明本文方法与传统的变正则因子方法以及变步长方法相比有更快的收敛速度与更低的稳态误差.     

基于Holt指数平滑模型的地下水水质预测

地下水水质预测是地下水污染防治研究工作的重要组成部分。本文介绍了Holt指数平滑模型的基本原理及平滑参数的确定方法,在此基础上,以阿拉善腰坝绿洲地下水水质预测为实例对地下水HCO3-、Cl-、SO42-和TDS进行了预测,并与灰色模型预测结果进行了对比。结果表明2006年HCO3-、Cl-、SO42-和TDS浓度值将分别达到198．260、77．290、114．850和508mg／L。应查清地下水各种污染源及各污染源对地下水水质的影响程度,以便采取有效措施,遏制地下水水质进-步恶化。Holt指数平滑模型统-考虑了所有已有时间序列资料对预测值的影响,提高了预测精唐．适用于已有较长时间序列资料前提下的预测。     

步进电动机加速控制算法研究及仿真

针对步进电动机在启动、停止时,会出现启动失步、堵转以及超程或冲击大等现象,提出了指数加减速算法和S形曲线加减速算法。首先建立了步进电动机的数学模型和传递函数。鉴于加速启动和减速停止过程是对称的,故笔者仅研究分析了对步进电动机启动阶段进行加速控制的过程。介绍了指数加减速算法和S形曲线加减速算法原理和设计方法,并应用Matlab实现了系统设计与仿真。最后对指数加速控制和S形曲线加速控制的仿真结果进行对比分析,结果表明:与指数加减速算法相比,S形曲线加速控制方法速度过渡光滑,具有更好的动、静态性能,且易于调整和改进。     

Periodic autoregressive conditional duration

We propose an autoregressive conditional duration (ACD) model with periodic time-varying parameters and multiplicative error form. We name this model periodic autoregressive conditional duration (PACD). First, we study the stability properties and the moment structures of it. Second, we estimate the model parameters, using (profile and two-stage) Gamma quasi-maximum likelihood estimates (QMLEs), the asymptotic properties of which are examined under general regularity conditions. Our estimation method encompasses the exponential QMLE, as a particular case. The proposed methodology is illustrated with simulated data and two empirical applications on forecasting Bitcoin trading volume and realized volatility. We found that the PACD produces better in-sample and out-of-sample forecasts than the standard ACD.